In the wake of the September 2001 attacks and mailing of anthrax-laced envelopes, policymakers and the public have become increasingly more concerned with bioterrorism and the emergence of disease-causing organisms (pathogens). Currently, computational models indicate the social effect of such pathogens on a human population. However, to understand how these diseases work, and to effectively aid emergency responders in any epidemic or bioterrorist attacks, a model needs to be developed to predict what may happen to and within a person when a person becomes infected.
The onset, duration and outcome of a disease state or infection are complex dynamic processes that are mediated by interactive responses in which both the pathogen and the infected host play opposing roles. Pathogenic mechanisms are normally investigated using laboratory (in vitro) and live (in vivo) studies. The in vitro approach provides a means of investigating and testing the pathogenic mechanism using components of the host against which the pathogen demonstrates a virulence effect. In vivo studies, using natural hosts or genetic variants (mutants) that exhibit modified susceptibility, provide data on living systems.
Specific in vivo studies may include either outcome observations using the intact host or directed observation of host components after onset of the disease. The use of in vitro and in vivo studies, while providing a sound basis for the study of the host-pathogen interaction in the disease, each exhibit limitations. It is also frequently difficult to link the in vitro (mechanistic) studies to the in vivo observations. Furthermore, for some diseases (e.g., human diseases like anthrax) the lethal effects on the test subjects precludes in vivo studies that involve human (host) exposure to a disease-causing organism (pathogen). Nonetheless, the ability to understand and describe the host-pathogen interaction is a key factor in enabling practitioners to test the current intervention strategies and possibly devise strategies based on simulation studies.
Consequently, it would be desirable to have a model that can simulate what may happen to an individual when that individual is exposed to the pathogen or contracts a disease. Not only can such model facilitate a better understanding of the potential effects that a pathogen may have on a person, but it can also provide a time range as to how much time emergency responders or medical practitioners have to save an individual before life-threatening symptoms manifest. Moreover, such a model can help perform “what if” studies and develop testable hypotheses concerning a host-pathogen relationship. It would also be desirable to have a computational model to predict host-pathogen interactions that would ease concerns regarding animal testing. In addition, it would be desirable to have such a model to save hours of research time and costs.